---
license: apache-2.0
base_model: google/bert_uncased_L-8_H-512_A-8
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: bert_uncased_L-8_H-512_A-8_massive
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: massive
      type: massive
      config: en-US
      split: validation
      args: en-US
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8839153959665519
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert_uncased_L-8_H-512_A-8_massive

This model is a fine-tuned version of [google/bert_uncased_L-8_H-512_A-8](https://huggingface.co/google/bert_uncased_L-8_H-512_A-8) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6061
- Accuracy: 0.8839

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 33
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.4813        | 1.0   | 180  | 1.3295          | 0.7506   |
| 1.0577        | 2.0   | 360  | 0.7897          | 0.8318   |
| 0.6168        | 3.0   | 540  | 0.6254          | 0.8623   |
| 0.404         | 4.0   | 720  | 0.5679          | 0.8672   |
| 0.2787        | 5.0   | 900  | 0.5594          | 0.8647   |
| 0.1993        | 6.0   | 1080 | 0.5499          | 0.8746   |
| 0.1406        | 7.0   | 1260 | 0.5674          | 0.8706   |
| 0.1044        | 8.0   | 1440 | 0.5678          | 0.8770   |
| 0.0775        | 9.0   | 1620 | 0.5668          | 0.8829   |
| 0.0565        | 10.0  | 1800 | 0.5830          | 0.8829   |
| 0.044         | 11.0  | 1980 | 0.6016          | 0.8785   |
| 0.0342        | 12.0  | 2160 | 0.6061          | 0.8839   |
| 0.0298        | 13.0  | 2340 | 0.6151          | 0.8815   |
| 0.0247        | 14.0  | 2520 | 0.6126          | 0.8810   |
| 0.0208        | 15.0  | 2700 | 0.6156          | 0.8829   |


### Framework versions

- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1